Senior GPU Storage Architect for AI Cloud
Bitdeer
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Benefits offered by this job
Job summary
Bitdeer is seeking an experienced storage operations engineer to own and optimize scalable HPC storage for AI workloads. You will deploy and manage multi-tenant storage, tune performance, and shape capacity planning for GPU clusters while integrating with NFS over RDMA, NVMe-oF, and related networking.
The role requires hands-on experience with WEKA, VAST Data, Ceph, and DDN/Lustre, strong Linux knowledge, and a drive to turn monitoring signals into automated runbooks and reliable visibility
Qualifications
- 5+ years in enterprise or HPC storage operations required.
- Hands-on deployment and operations with WEKA, VAST Data, Ceph or DDN/Lustre.
- Strong Linux systems knowledge (kernel tuning, filesystem internals).
- Experience with multi-tenant storage isolation and QoS.
- Familiarity with AI training I/O patterns and high-performance storage networking.
Responsibilities
- Deploy and operate parallel/distributed storage systems and design architectures for AI workloads.
- Implement multi-tenant storage isolation with per-tenant QoS and access controls; optimize GPU Direct Storage paths.
- Deploy and manage storage networking (NFS over RDMA, NVMe-oF) and cluster-wide storage orchestration.
- Diagnose and tune storage performance (IOPS, throughput, latency) and own runbooks for failure modes.
- Plan storage capacity aligned with GPU cluster growth and DR procedures.
Skills
Tools
Job description
Bitdeer is seeking an experienced storage operations engineer to own and optimize scalable HPC storage for AI workloads. You will deploy and manage multi-tenant storage, tune performance, and shape capacity planning for GPU clusters while integrating with NFS over RDMA, NVMe-oF, and related networking.
The role requires hands-on experience with WEKA, VAST Data, Ceph, and DDN/Lustre, strong Linux knowledge, and a drive to turn monitoring signals into automated runbooks and reliable visibility
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